AI Act - Navigating the key requirements
Delve into the EU AI Act’s framework with this comprehensive course, offering in-depth insights on compliance, systemic risks, GDPR considerations, and the development of AI policies.
This specialized course offers a deep dive into the EU AI Act. Modules cover a range of pressing topics, from understanding the AI Act key requirements to identifying potential AI harms and understanding the importance of AI literacy and data quality. Additionally, participants will gain practical knowledge on the interplay between the AI Act and GDPR.
By the end of this course, attendees will be equipped to navigate the AI Act confidently, implement compliant practices, and foster responsible AI literacy across their organizations. This training is ideal for those seeking an actionable roadmap to meet current and emerging AI regulatory standards.
Content
1. AI 101 (Introduction)
What is Artificial Intelligence?
Dive into General Purpose Systems (Foundation Models)
Navigating Systemic Risks and their Guardrails
AI Systems Development Lifecycle
Unveiling Prohibited AI Applications
Exploring High-Risk AI Applications
2. AI Act: Introduction and Timeline
The Legal Landscape of AI in the European Union
Understanding the AI Act’s Ecosystem and Scope
Key Milestones and Implementation Timeline
Defining Key Roles Under the AI Act
3. Key Requirements - Part I (Limited Risk, General Purpose Systems)
Characteristics and Legal Obligations for Limited Risk AI Systems
Overview of the Key Requirements of General-Purpose AI Systems
Managing General Purpose AI Systems with Systemic Risks
4. Key Requirements - Part II (Prohibited, High-Risk Systems)
Essential Requirements for Providers of High-Risk AI Systems
Key Responsibilities for Deployers of High-Risk AI Systems
Prohibited AI Systems: General Ban and Limited Exceptions
5. AI Literacy
Why AI Literacy Matters
Building AI Literacy Among Employees
Grasping AI Capabilities and Limitations
Managing Risks in AI Systems
Organizational Adaptation to AI
6. Potential Harms
Identifying and Understanding Potential AI Harms
Structuring AI Harms
7. How Quality Data Can Help to Avoid Bias
Data Quality in the AI Act
Introduction to Different Types of Bias
Best Practices for Mitigating Bias in AI
8. Interplay with GDPR
The Role of the Data Protection Officer (DPO)
Comparing DPIA, Conformity Assessment, and FRIA
Upholding Data Subjects’ Rights
Navigating Automated Decision Making (Article 22 GDPR)
Learning Outcomes
By the end of this seminar, participants will:
Understand the key requirements of the AI Act
Identify the main risks related to AI use
Learn how to develop and implement AI policies
Gain insights into GDPR requirements for AI
Training Method
The training will be conducted through interactive presentations and discussions led by two ELSI (Ethical, legal and social implications) specialists and a Data Scientist from LNDS. Participants will engage in Q&A sessions to clarify doubts and gain deeper insights.
Organised By
Digital Learning Hub Luxembourg
Certification
Participation OnlyPrerequisites
This seminar is designed for professionals responsible for deploying AI systems or developing policies and procedures related to AI usage within their organizations. No prior knowledge of the AI Act is required, but a basic understanding of AI and GDPR will be beneficial.
Your trainer(s) for this course

Magdalena VIDIS
